Hello,
I've analyzed some single and paired-end reads that were aligned to the human genome using TopHat and then put them through the htseq-count to DESeq pipeline. A clustering analysis of the variance-stabilized transformed count data (thank you Simon!) suggests that the differences between library types (single vs paired-end) are much bigger than the very significant differences between biological conditions.
Why might the count data between single and paired-end library types be so different?
Thanks,
Danielle
I've analyzed some single and paired-end reads that were aligned to the human genome using TopHat and then put them through the htseq-count to DESeq pipeline. A clustering analysis of the variance-stabilized transformed count data (thank you Simon!) suggests that the differences between library types (single vs paired-end) are much bigger than the very significant differences between biological conditions.
Why might the count data between single and paired-end library types be so different?
Thanks,
Danielle
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